python - 整个数据帧中 FOR 循环中的 IF 语句 : performance improvement

Question

我在整个 pandas 数据帧的 for 循环中使用 if 语句，但处理时间太长。有没有办法在不使用 for 循环的情况下执行此操作？

for i in data.index:
    if data['qt_CNAE'][i] > 20:
        data['CNAEuse'][i]=data['CNAE'][i]
        data['CNAEuse_Cres'][i]=data['Crescimento_CNAE'][i]

Answer 1

我认为需要双 numpy.where :

mask = data['qt_CNAE'] > 20
data['CNAEuse']= np.where(mask, data['CNAE'], data['CNAEuse'])
data['CNAEuse_Cres']=np.where(mask, data['Crescimento_CNAE'], data['CNAEuse_Cres'])

或者更好地使用numpy广播:

mask = data['qt_CNAE'] > 20
df[['CNAEuse','CNAEuse_Cres']] =(np.where(mask[:, None],
                                          df[['CNAE','Crescimento_CNAE']], 
                                          df[['CNAEuse','CNAEuse_Cres']]))

示例:

df = pd.DataFrame({'A':list('abcdef'),
                   'B':[4,5,4,5,5,4],
                   'C':[7,8,9,4,2,3],
                   'D':[1,3,5,7,1,0],
                   'E':[5,3,6,9,2,4],
                   'F':list('aaabbb')})

print (df)
   A  B  C  D  E  F
0  a  4  7  1  5  a
1  b  5  8  3  3  a
2  c  4  9  5  6  a
3  d  5  4  7  9  b
4  e  5  2  1  2  b
5  f  4  3  0  4  b

mask = df.F == 'a'
df[['B','D']] = np.where(mask[:, None], df[['C','E']], df[['B','D']])
print (df)
   A  B  C  D  E  F
0  a  7  7  5  5  a
1  b  8  8  3  3  a
2  c  9  9  6  6  a
3  d  5  4  7  9  b
4  e  5  2  1  2  b
5  f  4  3  0  4  b